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Dandelion Optimizer and Gold Rush Optimizer Algorithm-Based Optimization of Multilevel Inverters
With the increasing integration of renewable energy sources into distribution and transmission networks, the efficiency of cascade H-bridge...
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Effective long-term tracking with contrast optimizer
The main challenge of long-term tracking includes data uncertainty in long-term observations. Previous methods tackle the long-term tracking task by...
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Equilibrium optimizer: a comprehensive survey
Equilibrium optimizer (EO) is a recent optimization method inspired by the physical equation of the mass balance that provides the conservation of...
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Fractional-Order Water Flow Optimizer
The water flow optimizer (WFO) is the latest swarm intelligence algorithm inspired by the shape of water flow. Its advantages of simplicity,...
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A blueprint for a synthetic genetic feedback optimizer
Biomolecular control enables leveraging cells as biomanufacturing factories. Despite recent advancements, we currently lack genetically encoded...
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Chaotic-Based Mountain Gazelle Optimizer for Solving Optimization Problems
The Mountain Gazelle Optimizer (MGO) algorithm has become one of the most prominent swarm-inspired meta-heuristic algorithms because of its...
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Density-based topology optimization with the Null Space Optimizer: a tutorial and a comparison
The Null Space Optimizer is a constrained optimization solver that has been developed in the context of level-set-based Topology Optimization. One of...
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Digital Channel Equalizer Using Functional Link Artificial Neural Network Trained with Quantum Aquila Optimizer
In digital communication, channel equalization plays an important role in mitigating the effects of inter-symbol interference, non-linearity and...
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CQND-WHO: chaotic quantum nonlinear differential wild horse optimizer
Wild horse optimizer (WHO) features a simple structure with few parameters, facilitating fast convergence. However, it suffers from low global search...
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Augmented weighted K-means grey wolf optimizer: An enhanced metaheuristic algorithm for data clustering problems
This study presents the K-means clustering-based grey wolf optimizer, a new algorithm intended to improve the optimization capabilities of the...
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ILO: An Improved Lemur Optimizer for Global Optimization
The lemur optimizer (LO) is a new metaheuristic algorithm that is inspired by the two primary locomotive patterns of the lemurs. However, LO suffers...
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Lero : applying learning-to-rank in query optimizerIn recent studies, machine learning techniques have been employed to support or enhance cost-based query optimizers in DBMS. Although these...
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Boosting manta rays foraging optimizer by trigonometry operators: a case study on medical dataset
The selection of attributes has become a crucial research focus in the domains of pattern recognition, machine learning, and big data analysis. In...
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Solving time cost optimization problem with adaptive multi-verse optimizer
The construction industry holds a central role globally, marked by its unique attributes that lead to distinct challenges. Given projects in this...
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Enhanced handwritten digit recognition using optimally selected optimizer for an ANN
Handwritten digit recognition is a complex problem that has stumped even the brilliant minds of this century. Getting precise results from different...
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Novel Optimizer MAdam for Efficient Fruit Grading and Quality Assessment Using CNN-LSTM
Traditional grading and sorting of fruits is a time-consuming process that demands skilled labor. So, the use of computer vision and machine learning...
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Enhanced Aquila optimizer based on tent chaotic map** and new rules
Metaheuristic algorithms, widely applied across various domains due to their simplicity and strong optimization capabilities, play a crucial role in...
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Electrical parameters extraction of PV modules using artificial hummingbird optimizer
The parameter extraction of PV models is a nonlinear and multi-model optimization problem. However, it is essential to correctly estimate the...
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Enhanced gorilla troops optimizer powered by marine predator algorithm: global optimization and engineering design
This study presents an advanced metaheuristic approach termed the Enhanced Gorilla Troops Optimizer (EGTO), which builds upon the Marine Predators...
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Chaotic gradient based optimizer for solving multidimensional unconstrained and constrained optimization problems
Gradient-based optimizer (GRAD) belongs to the recently developed population-based metaheuristic algorithms inspired by the development of...
